The present study is aimed at optimizing the Material Removal Rate (MRR), Surface Roughness (SR) and Tool Wear Rate (TWR) of die sinking Electrical Discharge Machining (EDM) by considering the simultaneous affect of various input parameters. The experiments are carried out on 40CrMnMoS86 hot worked steel parts. Experiments were conducted by varying the peak current (I), voltage (V), pulse on time (Ton), pulse off time (Toff) and duty factor (h). The corresponding values of material removal rate, tool wear rate and surface roughness were measured. The relation between machining parameters and performance can be found out with the Grey Relational Analysis (GRA). Developed multi objective model is optimized by Simulated Annealing algorithm (SA) and machiningoptimal parameters setting is found. A confirmation test is also performed to verify the effectiveness of optimization procedure in determining the optimum levels of machining parameters. The consequences show that the combination of Taguchi technique, grey relational analysis and simulated annealing algorithm is quite efficient in determining optimal EDM process parameters.

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